Evaluation of WWTP loads into a Mediterranean river using KSOM neural networks and simulation mass balance modelling

Abstract : The water quality of the Têt River, mainly referred to nutrients and organic matter compounds, is lower than the desirable. Their management must be largely improved. In this sense, the present work takes part in a global development and evaluation of reliable and robust tools, with the aim of allowing the control and supervision of its lowland area (at the south Mediterranean coast of France). A simplified simulation model, based on mass balances, has been developed to estimate nutrient (basically, nitrogen) and organic matter levels in the stream and to describe the river water quality. Kohonen self-organizing maps (KSOMs) were used to avoid the data missing. This kind of neural networks proved to be very useful to predict missing components and to complete the available database, describing the chemical state of the river and the WasteWater Treatment Plant (WWTP) outflows. The simulation model also proved to be a good tool for the evaluated system. The results provided by it reveal the high impact of the WWTPs located along the studied reach, due to their malfunction and the effects of the tourism activities.
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Esther Llorens, Frédérik Thiéry, Stéphane Grieu. Evaluation of WWTP loads into a Mediterranean river using KSOM neural networks and simulation mass balance modelling. Chemical Engineering Journal, Elsevier, 2008, 142 (2), pp.135-146. ⟨http://www.sciencedirect.com/science/article/pii/S1385894707007644⟩. ⟨hal-01273240⟩

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